Impact of Pharmacist-led Discharge Counseling on Hospital Readmission and Emergency Department Visits: A Systematic Review and Meta-analysis

Emergency Department Visit Rates

A total of eight studies evaluating the impact of pharmacist-led discharge counseling on emergency department visits were included in the meta-analysis.^{21,22,24,26,32-34,39} For the study by Farris et al., we used data from the “minimal intervention” branch.²⁶ Although the original results showed differences between intervention and usual care (RR = 0.697 [95% CI 0.535-0.907], P = .007; Figure 3), the meta-analysis presented high heterogeneity with an I² value of 58.86% (Tau = 0.265; PI 0.027-1.367). Sensitivity analyses with the hypothetical removal of studies did not modify the original results (I² values ranging from 26.05% to 64.74%).

Subgroup analyses considering time of evaluation of the outcome were possible for studies of one, three, and six months postdischarge (Supplemental Material). No statistical differences were observed for the subgroup of one month (RR = 0.705 [95% CI 0.449-1.106] with the original I² = 65.5%). Sensitivity analyses showed that the study by Phatak et al. was responsible for the high heterogeneity (results of I² = 38% after removing this trial),³² without significant changes in the effect sizes. The three-month subgroup included only two studies and presented an RR of 0.763 (95% CI 0.599-0.972, P = .028).^21,26 However, sensitivity analysis based on statistical modifications in the model altered the results, and no differences between the intervention and usual care were truly observed (eg, using the inverse variance method, the random model produced an odds ratio of 0.575 [95% CI 0.219-1.512]). Pharmacist-led counseling reduced the number of emergency department visits at six months postdischarge, RR = 0.605 (95% CI 0.459-0.768, P = .001), but only two studies were included in this analysis.^33,39

The present systematic review and meta-analysis showed equivocal results on the effect of pharmacist-led discharge counseling compared with usual care in reducing the number of hospital readmissions and emergency department visits. Although some of the meta-analyses slightly favored pharmacist interventions, the small number of primary studies included and the moderate-to-high heterogeneity among trials prevented drawing further conclusions. Moreover, sensitivity analyses and PIs revealed no true differences between the intervention and usual care.

Pharmacist interventions are generally complex, being constituted by several components,⁴¹ which are frequently poorly described in the literature and generally inconsistently performed.^42-44 These factors can contribute to reduced methodological quality and enhanced heterogeneity, as reported in previous systematic reviews and meta-analyses.^8,42,45-47 Moreover, the characteristics of the included patients (eg, different clinical conditions) and the small sample sizes may have increased heterogeneity among trials in our meta-analyses.

Similar to our results, El Hajj et al. were not able to demonstrate significant differences between usual care and pharmacist interventions in the transition of care (eg, medication reconciliation, medication therapy management, discharge medication counseling, motivational interviewing, and postdischarge face-to-face or telephone follow-up) in reducing rates of hospital readmission, visits to emergency units, and mortality, or in improving medication adherence.¹¹ Another systematic review with a meta-analysis also showed that interventions, including discharge counseling, did not reduce the number of hospital readmissions (RR = 0.97 [95% CI 0.89-1.05], P = .470) and visits to emergency units (RR = 0.70 [95% CI 0.59-0.85] P = .001).⁴⁸ However, both systematic reviews included few RCTs with moderate methodological quality, which may compromise interpretation of the results. In this case, imprecision in estimates and individual study results may be more informative than a meta-analysis.

Ensing et al. highlighted the need for more well-designed RCTs for clinical pharmacy services to provide high-quality information to be included in systematic reviews and meta-analyses.⁴⁹ This may enable the identification of the true effect of pharmacist interventions in patient care.⁴⁰ In our systematic review, the high risk of bias in some included studies was attributed especially to the attrition domain, indicating that the outcomes were poorly evaluated or patient losses and withdrawals were not sufficiently described. In addition, most of the studies had an unclear risk of bias, primarily because of poor descriptions of the blindness of the outcome assessors. These pitfalls highlight the need for more rigorous standards for carrying out and reporting RCTs on pharmacist interventions, which should be strictly required by journal editors and reviewers.⁵⁰Moreover, the standardization of outcomes is also important to allow comparability between studies. Core outcome sets represent agreed sets of outcomes that should be measured and reported by trials in a specific area, as recommend by the COMET Initiative (Core Outcome Measures in Effectiveness Trials).⁵¹ Pharmacy practice studies have started defining core outcome sets to be used in future trials,^52-54 as recently happened for pharmacist-led discharge counseling.⁵⁵ It is important to keep in mind the different implications resulting from the use of endpoint outcomes, surrogate outcomes, or process indicators. Although the latter are easily measured but also easily influenced by interventions, endpoint outcomes represent the real impact of the interventions that should be used in economic evaluations.⁵⁶ Surrogate outcomes are frequently used as a proxy of endpoint outcomes, but precaution is needed when inferring conclusions.⁵⁷ In our study, we preferred using healthcare services utilization as a measure of intervention success. However, these outcomes could also be affected by other factors not related to medication safety. The use of properly designed RCTs and their synthesis in robust meta-analyses should minimize potential interpretation biases.

Our findings also show the need to better define clinical pharmacy services. A better description of interventions is important to not only allow evidence gathering but also enable the proper replication of complex interventions in practice and to ground further analyses on the economic impact of pharmacist interventions.

Our study has some limitations. Although subgroup and sensitivity analyses were performed, we were not able to reduce the heterogeneity and effect size intervals of some meta-analyses. Caution should be used when interpreting the results from the subgroup meta-analysis, including small numbers of studies (n = 2-4). The absent or minor effects of pharmacist-led interventions on healthcare services utilization found in our study may be due to a real lack of measurable effect of the intervention itself or due to the limited evidence available in the literature. This is related to the small number of primary studies, poor reporting practices, and high heterogeneity between trials. In addition, another limitation that affects our study is the poor measurement of intervention fidelity in primary studies, which precludes an in-depth analysis of the effect of the different intervention components. A better report of intervention fidelity would allow a different sensitive analysis that could differentiate the most successful interventions.

Similar to what happens with other complex interventions by pharmacists, a detailed description of the procedure, together with reporting on a core outcome set, is needed to enhance reproducibility. Future RCTs of clinical pharmacy services that follow standard protocols such as DEPICT⁵⁸ and CONSORT⁵⁹ and report in detail how the study and the interventions were performed will contribute to more robust evidence generation.